Analysis of agricultural greenhouse gas emissions using the STIRPAT model: a case study of Bangladesh.

ABSTRACT: The agriculture sector is one of the leading emitters of greenhouse gases in Bangladesh, owing to increasing mechanization, changing population patterns and increasing cultivation of irrigation intensive crops like rice. The objective of this research is to analyze how population trends, energy use and land use practices impact the emissions of three greenhouse gases from the agriculture sector in Bangladesh. The gases studied are carbon dioxide, methane and nitrous oxide. The Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and ridge regression are used to analyze the drivers of emissions covering the period from 1990 to 2014. Explanatory factors of emissions are the total and rural population, affluence, urbanization, fertilizer intensity and quantity, carbon and energy intensity, irrigation, rice cultivation, cultivated land and crop yield. The findings reveal that the country's total population has a negative effect, and the rural population has a negative, nonlinear impact on the emissions of methane. Affluence affects emissions of all the gases. The energy intensity and carbon intensity of agriculture increase carbon dioxide emissions. The cultivated land area, rice cultivation quantity and crop yield increase methane emissions, while irrigated land area decreases it. Rural population, total population and urbanization have a positive linear effect on carbon dioxide and nitrous oxide emissions. Fertilizer quantity and intensity increase nitrous oxide emissions. The findings imply that increasing agricultural mechanization should be based on clean energy, and land management should be regulated to enable the country to meet its Nationally Determined Contribution (NDC) targets as well as the targets of Sustainable Development Goal (SDG) 7 of increasing the share of clean energy.

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SUBMITTER: Aziz S 

PROVIDER: S-EPMC9301621 | biostudies-literature |

REPOSITORIES: biostudies-literature